Data releases may be subject to de-anonymization attacks. De-anonymization attacks may attempt to identify individuals associated with some particular released data. Individuals may be associated with the data even in instances where traditionally personal identifiers, such as names, telephone numbers, addresses, social security numbers and/or other unique identification numbers, or the like, are absent. For example, it has been observed that approximately 87 percent of the population of the United States may be uniquely identified based on a gender, a date of birth, and a 5-digit residence zip code. Thus, anonymity may not be achieved even when data may not include traditional identifiers for individuals associated with the data.
The subject matter claimed herein is not limited to embodiments that solve any disadvantages or that operate only in environments such as those described above. Rather, this background is only provided to illustrate one example technology area where some embodiments described herein may be practiced.